Systems and methods of livestock management

ABSTRACT

A system and method of livestock management comprising a device disposed in a livestock animal. The device comprises a network interface, a housing defining a cavity, a weighted element, a power supply, a data processing unit, a temperature sensor and an accelerometer. The temperature sensor acquires temperature data of the livestock animal. The accelerometer acquires movement data of the livestock animal. The cavity includes a data processing system having at least one processor and memory. The data processing system is coupled with the power source and communicatively coupled with the temperature sensor and the accelerometer. The data processing system transmits, via the network interface, temperature data and movement data. The cavity includes an activation receiver to receive activation signal to activate the data processing system. A livestock management server receives and analyzes the data, along with any data from any additional data sources, and provides output to a user interface.

CROSS REFERENCE TO RELATED APPLICATIONS

The application claims priority to and the benefit of U.S. ProvisionalPatent Application Ser. No. 63/248,974, entitled “SYSTEMS AND METHODS OFLIVESTOCK MANAGEMENT” filed on Sep. 27, 2021, the disclosure of which isincorporated herein by reference in its entirety.

BACKGROUND

It is difficult to manage livestock animals such as cattle, horses,sheep, goats and pig. Livestock tags, collars, and leg-bands that attachto animal ears have been used, but they can be large and do not fit ontoyounger animals such as calves. Furthermore, the identification tags canbe moved among the animals to fake the history of the animals. Usersmanually enter the tags into a system to link the tag to an animal,which can make it difficult to utilize an animal identificationsolution.

There is a desire to provide advanced means to track livestock animalswith reduced risk of tampering, and further, to obtain, monitor andtrack information about each livestock animal.

SUMMARY

At least one aspect is directed to a device to dispose within alivestock animal. The device can include a network interface. The devicecan include a housing that defines a cavity. The cavity can includedisposed therein an identification tag. The cavity can include disposedtherein a weighted element disposed at a first end of the cavity. Thecavity can include disposed therein a power source comprising acapacitor and a battery. The cavity can include disposed therein atemperature sensor coupled with the power source. The temperature sensorcan acquire temperature data of the livestock animal. The cavity caninclude disposed therein an accelerometer coupled with the power source.The accelerometer can acquire movement data of the livestock animal. Thecavity can include disposed therein a data processing system having atleast one processor and memory. The data processing system can becoupled with the power source and communicatively coupled with thetemperature sensor and the accelerometer. The data processing system cantransmit, via the network interface, the temperature data and themovement data. The cavity can include disposed therein an activationreceiver to receive an activation signal to activate the data processingsystem.

The activation receiver including a magnet. The memory can store thetemperature data and the movement data. The data processing system canacquire the temperature data and the movement data responsive to theactivation signal. The housing can include a machine-readable opticallabel such as a QR code. The capacitor can have a capacitance of atleast 1 Farad. The housing can have a weight between 50 and 500 grams.The housing can include polyethylene or polypropylene. The housing caninclude a width of 20 mm and a length of 70 mm. The device can bedisposed in a gastrointestinal tract of the livestock animal.

At least one aspect is directed to a device to manage livestock. Thedevice can include a data processing system having one or moreprocessors coupled with memory. The data processing system can receive,from an activation receiver, an activation signal to activate the one ormore processors. The data processing system can transmit, responsive tothe activation signal, via a network interface, to a livestockmanagement server, a connection request to establish a connection withthe livestock management server. The data processing system can receive,from a temperature sensor of the device, temperature data of a livestockanimal. The data processing system can receive, from an accelerometer ofthe device, movement data of the livestock animal. The data processingsystem can store, in the memory of the data processing system, thetemperature data and the movement data. The data processing system cantransmit, via the network interface using the connection with thelivestock management server, at a predetermined time interval, thetemperature data and the movement data.

The data processing system can receive, from the livestock managementserver, an acknowledgment of transmitting the temperature data and themovement data. The data processing system can identify an errorsubsequent to transmitting the temperature data and the movement data.The data processing system can receive, from the temperature sensor ofthe device, additional temperature data of the livestock animal. Thedata processing system can receive, from the accelerometer of thedevice, additional movement data of the livestock animal. The dataprocessing system can transmit, responsive to the activation signal, viathe network interface, to the livestock management server, a secondconnection request to establish a second connection with the livestockmanagement server. The data processing system can transmit, via thenetwork interface using the second connection with the livestockmanagement server, at the predetermined time interval, the temperaturedata, the movement data, the additional temperature data, and theadditional movement data. The data processing system can receive, at afirst predetermined time interval, the temperature data from thetemperature sensor. The data processing system can receive, at the firstpredetermined time interval, the movement data from the accelerometer.The data processing system can store the temperature data and themovement data in the memory. The data processing system can generate, ata second predetermined time interval, a data packet including thetemperature data and the movement data stored in the memory. The dataprocessing system can transmit the data packet including the temperaturedata and the movement data.

At least one aspect is directed to a system to monitor livestockanimals. The system can include a herd database to maintain livestockanimal information of one or more livestock animals in a herd. Thesystem can include a data processing system having at least oneprocessor coupled with memory. The data processing system can receive,from a livestock management device disposed within a livestock animal, aconnection request, the connection request including an identifier ofthe livestock management device. The data processing system canidentify, from the identifier of the livestock management device, thelivestock animal corresponding to the livestock management device. Thedata processing system can receive, from the livestock managementdevice, temperature data and movement data of the livestock animal. Thedata processing system can generate a comparison between the livestockanimal information maintained by the herd database and the temperaturedata and movement data of the livestock animal. The data processingsystem can identify, based on the comparison, estimated characteristicsof the livestock animal. The data processing system can transmit theestimated characteristics of the livestock animal to a user interface.The data processing system can receive, from the user interface, anidentification of the characteristic of the livestock animal. The dataprocessing system can modify the analysis based on the identification.

The data processing system can receive a data packet including thetemperature data and movement data of the livestock animal. Theidentifier can be a QR code or some other machine-readable optical code.

At least one aspect is directed to a method of managing a livestockanimal. The method can include scanning an identifier of a device, thedevice comprising a housing that defines a cavity. The cavity caninclude disposed therein an identification tag. The cavity can includedisposed therein a weighted element disposed at a first end of thecavity. The cavity can include disposed therein a power sourcecomprising a capacitor and a battery. The cavity can include disposedtherein a temperature sensor coupled with the power source, thetemperature sensor to acquire temperature data of the livestock animal.The cavity can include disposed therein an accelerometer coupled withthe power source. The accelerometer can acquire movement data of thelivestock animal. The cavity can include disposed therein a dataprocessing system having at least one processor and memory. The dataprocessing system can be coupled with the power source andcommunicatively coupled with the temperature sensor and theaccelerometer. The data processing system can transmit, via the networkinterface, the temperature data and the movement data. The cavity caninclude disposed therein an activation receiver to receive an activationsignal to activate the one or more processor. The method can includeapplying, using a magnetic field, the activation signal to activate thedevice. The method can include introducing the activated device into agastrointestinal tract of the livestock animal. The method can includereceiving, in a user interface, an estimated characteristic of thelivestock animal. The method can include providing, via the userinterface, a confirmed characteristic of the livestock animal.

At least one aspect is directed to a method to monitor livestockanimals. The method can include maintaining, by a data processing systemhaving at least one processor coupled with memory, a herd databaseincluding livestock animal information of one or more livestock animalsin a herd. The method can include receiving, by the data processingsystem, from a livestock management device disposed within a livestockanimal, a connection request, the connection request including anidentifier of the livestock management device. The method can includeidentifying, by the data processing system, from the identifier of thelivestock management device, the livestock animal corresponding to thelivestock management device. The method can include receiving, by thedata processing system, from the livestock management device,temperature data and movement data of the livestock animal. The methodcan include generating, by the data processing system, a comparisonbetween the livestock animal information maintained by the herd databaseand the temperature data and movement data of the livestock animal. Themethod can include generating, by the data processing system, ananalysis of the comparison to identify estimated or predictedcharacteristics of the livestock animal. The method can includetransmitting the estimated or predicted characteristics of the livestockanimal to a user interface. The method can include receiving, by thedata processing system, from the user interface, a confirmedcharacteristic of the livestock animal determined through other systemsor algorithms, for instance by directly measuring the amount of feedconsumed by the livestock animal. The method can include modifying, bythe data processing system, the information maintained by the herddatabase based on the confirmed characteristic.

BRIEF DESCRIPTION OF THE DRAWINGS

Objects, aspects, features, and advantages disclosed herein will becomemore fully apparent from the following detailed description, theappended claims, and the accompanying drawing figures in which likereference numerals identify similar or identical elements. Referencenumerals that are introduced in the specification in association with adrawing figure may be repeated in one or more subsequent figures withoutadditional description in the specification in order to provide contextfor other features, and not every element may be labeled in everyfigure. The drawing figures are not necessarily to scale, emphasisinstead being placed upon illustrating principles and concepts. Thedrawings are not intended to limit the scope of the claims includedherewith.

FIG. 1 is a depiction of an embodiment of a device to dispose within alivestock animal.

FIG. 2 is a logical diagram of an embodiment of a device to disposewithin a livestock animal.

FIG. 3 is a depiction of a reed switch of the device.

FIG. 4 is a depiction of an assembly of the reed switch of the device;

FIG. 5 depicts charging the capacitor of the device;

FIG. 6 is a depiction of the housing of an embodiment of the device;

FIG. 7 is a depiction of the housing of an embodiment of the devicefeaturing a machine-readable optical label;

FIG. 8 is a depiction of a weighted element;

FIG. 9 is a depiction of the assembled housing of an embodiment of thedevice;

FIG. 10 depicts a firmware component diagram;

FIG. 11 depicts a firmware state diagram;

FIGS. 12 and 13 depict flow diagrams of activating the device;

FIG. 14 depicts a flow diagram for sending data from the accelerometer;

FIG. 15 depicts a network diagram for a livestock management server; and

FIGS. 16 and 17 depict user interfaces for displaying livestock animalcharacteristics.

DETAILED DESCRIPTION

The present disclosure overcomes previous challenges by providingsystems and methods of livestock management. Provided is a device withsensors for monitoring health and characteristic of livestock animals.The device can be sized to be small enough to be ingested by thelivestock animals but large enough to be retained within the animal. Thedevice can include epoxy that covers all the components inside the bolusto make it durable (e.g., such as if bitten by the livestock animal).The device (e.g., bolus) can monitor the livestock animals (e.g., cowsor calves) for a long time, such as 9 years. The device can include abattery and a super-capacitor to extend the lifetime of the device. Anoperator (e.g., farmer) can scan an identifier (e.g., QR code or someother machine-readable optical label) located on the body of the deviceto read it with a scanner (e.g., mobile phone camera orapplication-specific device) to link the device with a livestock animalidentifier before having the livestock animal ingest the device.Therefore, the operator can easily initialize monitoring the livestockanimal without requiring technicians or invasive procedures on thelivestock animal.

The device can include a thermometer and accelerometer and othersensors, from which the device can acquire measurements at pre-setintervals. A microprocessor in the bolus can use machine-learning (ML)algorithms to extract valuable summary of the data from theaccelerometer. Once processed into a smaller size, suitable fortransition via low-power wide-area network protocol protocols (e.g.,LoRa), the device can send the data to a nearby gateway, which connectsto our cloud-computing platform via Internet (e.g., Wi-Fi at a farm). Bytransmitting the data at predetermined intervals, the device can reducepower consumption. By optimizing the power consumption, the device canhave improved battery life to the extent that the device can providedata from within the livestock animal for years.

On the server (e.g., livestock management server, one or more servers,cloud platform), ML algorithms can generate a profile and establish arange of normal parameters for each animal. If the data from a deviceshows deviation from the early established norms of this animal, anotification (e.g., alert) can be sent to the operator's personal device(e.g., cellphone) or user interface (e.g., web interface or portal). Thefarmer can provide feedback about the notification and the condition ofthe livestock animal. This feedback can be used by the server to trainthe ML algorithms to improve the accuracy of monitoring. Therefore, thesystem can incorporate the feedback and animal assessment protocols tocontinuously train the ML algorithms to improve the accuracy andrelevance of the alerts regarding the livestock animals.

FIG. 1 depicts a device 100 for monitoring livestock animals. The device100 can acquire health, characteristic, behavior, and identificationparameters of the livestock animal. A livestock animal can ingest thedevice 100. The device 100 can be waterproof and durable to resistphysical impact. For example, the device 100 can remain functional afterbeing dropped from a 2 meter height on the concrete floor. The device100 can include a weight to keep the device 100 at the bottom of thestomach of the livestock animal.

The device 100 can include a housing 105. The housing 105 can house thecomponents of the device 100. The housing 105 can have the shape of acapsule or a bullet. The housing 105 can be made out of plastic,high-density polyethylene (HPDE) or some other biocompatible material.The housing 105 can be filled with epoxy. The HPDE can have a densitybetween 0.83 to 1.07 g/cm³. For example, the housing 105 can house thebattery 115 so that it stays inside the housing 105 and does not leakinto the livestock animal. Even if the housing enclosure breaks orcracks, the housing 105 itself can remain solid to keep the componentsstable and operational.

The housing 105 can have a width of 20 mm and a length of 70 mm. Thewidth can be from 15 mm to 30 mm. The length can be greater than 70 mm,such as 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, or 200mm. A short length, such as 70 mm, allows for the bolus to beadministered to calves at birth, and to be administered to smalleranimals such as sheep or goats. The housing 105 can include anidentifier. The identifier can be an RFID tag or a Radio ID.

The housing 105 can include a weighted element 110. The weight of theweighted element 110 can be between 50 and 500 grams. The weight of theweighted element 110 can be 75 grams. The weighted element 110 can bedisposed at a tip of the device 100. For example, the weighted element110 can be disposed at a tip of the device 100 or the bottom of thedevice 100.

The housing 105 can include a unique identifier. The unique identifiercan be disposed on the housing. The unique identifier can be amachine-acquirable identifier such as a QR code or othermachine-readable optical label, a nearfield-readable radio-frequency tagsuch as RFID, or some other easily machine-acquirable identifier. Anoperator can scan the identifier to identify the device 100.

Referring to FIG. 2 , among others, the housing 105 can include a powersource 205. The power source 205 can be a battery. The battery can bedesigned for long-term applications. The battery can be a 1.65 Ahnon-rechargeable Lithium-thionyl-chloride battery, or a rechargeablebattery. The battery can provide power to the device 100 for years, suchas 4, 5, or 9 years. The shelf time of the non-activated device can beat least 2 years. The power source 205 can include a capacitor. Thecapacitor can include a capacitance. The capacitance can be more than 1Farad, such as 10 to 100 Farads.

The housing 105 can optionally include a switch mode power supply (SMPS)210 connected to the power source 205. If the SMPS 210 is not present,the battery and/or capacitor 205 may connect directly to the dataprocessing system 235.

The housing 105 can include a temperature sensor 215. The temperaturesensor 215 can be a pre-calibrated high-accuracy digital temperaturesensor integrated circuit having a 16-bit resolution with an accuracy of0.1 C and a communication protocol of I2C. The temperature sensor 215can measure temperatures in the range from +0 to +50 C. The temperaturesensor 215 can include an accuracy ±0.1° C. The temperature sensor 215can be coupled with the power source 205 or the power supply 210.

The housing can include an accelerometer 225. The accelerometer 225 canmeasure accelerometer data. The accelerometer 225 can be an ultra-small,triaxial, low-g high performance acceleration sensor with digitalinterfaces in a wearable device configuration. The accelerometer's 225range can be 4 g. The measurement rate can be 1.56 Hz. The resolutioncan be 16-bit per axis. The communication can be via I2C. For example,the accelerometer 225 can generate movement data. The movement data canbe indicative of movements of the livestock animal. The accelerometer225 can be coupled with the power source. When enabled, theaccelerometer 225 can perform a 3-axis measurement (e.g., 1 frame) atthe measurement rate. The accelerometer 225 can store the measurement inan internal memory (e.g., FIFO buffer). This data processing system canremain in sleep mode while measurements are taken until the memory isfilled. When the memory is full, an interrupt can trigger themicrocontroller to wake-up at a predetermined memory level, which canequal a predetermined number of frames. This corresponds to a wake-up atroutine intervals that can be beneficial for data collection. Theinterrupt can cause the microcontroller to read the memory from theaccelerometer and reset the memory.

The device 100 can include a network interface 220. The networkinterface 220 can comprise an antenna 235. The network interface 220 canbe a network dongle, such as a Wi-Fi, LoRa, or RFID. For example, theinterface 220 can be a low power, wide area (LPWA) adapter to operate onLPWA networks. The network interface 220 can have a transmission rangeof at least 25 meters or 350 meters from inside the livestock animal inwhich the device 100 is disposed. The operator can test the signalstrength of the network interface 220 to measure the reception range.The network interface 220 can be insulated from being affected by theactivation signal (e.g., magnetic field) during activation of the device100.

The housing can include an activation receiver 230 for activating thedevice 100. Before activation, the device 100 can be a in a standby mode(e.g., deep sleep mode) to conserve battery life. The activationreceiver 230 can receive an activation signal. The activation signal canbe a magnetic field received from a magnet. The activation receiver 230includes a magnet. The activation receiver 230 can generateinitialization signal or current responsive to the activation signal.The activation receiver 230 can be the network interface or configuredto be part of the network interface. Conversely, the network interface220 can be part of the activation receiver 230. The network interface220 and the activation receiver 230 can be distinct components.

The housing can include a data processing system 235. The dataprocessing system 235 can have at least one processor and memory. Thedata processing system 235 can be coupled with the temperature sensor215. The data processing system 235 can receive temperature data fromthe temperature sensor 215. The data processing system 235 can becoupled with receive movement data from the accelerometer 225. The dataprocessing system 235 can store the temperature data and the movementdata in the memory. The data processing system 235 can be coupled withthe network interface 220. The data processing system 235 can be coupledwith the power source 205 or with the SMPS 210. The data processingsystem 235 can be coupled with the activation receiver 230. The dataprocessing system 235 can be activated responsive to the receiving theactivation signal. For example, the data processing system 235 can drawpower from the SMPS 210 or power source 205 responsive to the activationsignal.

The device 100 can utilize temperature and accelerometer sensors tomonitor the health of livestock animals (e.g., ruminant animals such ascalves and cattle) from within the animal's reticulum or digestivetract. The data processing system 235 can transmit the temperature dataand the movement data via the network interface 220 to a livestockmanagement server. The livestock management server can use thetemperature data and the movement data to identify characteristics ofthe livestock animal. For example, the livestock management server canidentify that the livestock animal is eating, walking, running, jumping,ruminating, or is sick, stressed or in estrus.

The device 100 can be manufactured to IPC-A-610 Class 2. The assemblycan be performed by using ESD controlled procedures. The device 100 canbe programmed before the battery and capacitor are installed. Theassembly can be performed using surface-mount technology (SMT). NormalSMT processes can be followed to assemble the (Printed Circuit BoardAssembly) PCBA.

The device 100 can be programmed by ensuring that the ID range isreceived from the livestock management serve, or through other means.The antenna may be surface-mounted, through-hole assembled, wired to thePCB, or attached electrically to the PCB in some other way.

FIG. 3 depicts the reed switch 305 of the device 100 which may be usedfor activation. In other embodiments, other switch types, mountings orconfigurations may be used, or the device may not use a hardware switchat all. Specifically, a hall sensor may be used in place of a reedswitch.

FIG. 4 depicts the reed switch 305 mounted to the printed circuit boardassembly (PCBA) 405 of the device 100.

FIG. 5 depicts charging the capacitor of the device 100. Assembly of thedevice 100 can include charging the capacitor.

FIGS. 6-9 depict enclosing the electronic components in a housing 105 ofthe device 100.

Referring to FIG. 6 , among others, shown is the housing 105 (e.g.,capsule) of the device 100. The body can be made out of HPDE,polypropylene, or another material which may have similar qualitiesrelated to manufacturability or ingestibility. The body can be milktranslucent white, black or some other color. The electronic componentscan be inserted into the body and secured inside by an end cap.

Referring to FIG. 7 , among others, the operator can apply a label 705to the body of the housing 105. For example, the label can be amachine-readable optical label such as a QR code, or a uniqueidentifier. The operator can verify that the unique identifier on thelabel corresponds to the unique identifier of the PCBA 405. Using anEpoxy gun and static mixer, the operator can add Epoxy (e.g.,approximately 1 mL) to the housing to fill the rounded bottom of thehousing.

Referring to FIG. 8 , among others, depicted is a weighted element 805.The weighted element 805 can be a brass cylinder. The operator caninsert the weighted element 805 into the housing 105 and push the weightdown to the bottom of the housing 105.

Referring to FIG. 9 , among others, the operator can insert the PCBA 405into the housing 105. The operator can insert the PCBA such that batteryis adjacent to the weight 805 and the antenna is adjacent to the openend. The operator can use the epoxy gun and the static mixer to fill thecapsule with epoxy to leave enough space (e.g., approximately 2 mm) foran air gap after closing with the lid. In other embodiments, other waysof attaching the lid, such as ultrasonic welding, may be used.

The data processing system 235 can be programmed with firmware. Thefirmware can include functionality for measuring internal temperature,cattle activity level, and rumination. The firmware can collect themeasurements to identify secondary information about the livestockanimal such as water intake, feed intake and activity actions such asmovement. The firmware can place the device 100 in a deep sleep state(e.g., STM32 STOP mode). Prior to activation, the data processing systemcan receive the activation signal (e.g., application of the magnet) towake device 100. The data processing system can transmit a join requestresponsive to the activation signal. If the join request to the network(e.g., LoRa network, The Things Network, or Chirpstack) is unsuccessful,the device will reboot and re-enter deep sleep.

Once joined successfully, the device 100 can acquire a temperaturemeasurement and initialize accelerometer recording. At everypredetermined measurement interval (e.g., 5 minutes, 10 minutes, 15minutes, or 30 minutes), the data processing system acquires atemperature measurement and accelerometer data. After a predeterminednumber of intervals (e.g., 2 intervals or 30 minutes), a temperaturepacket can be sent. Various intervals may be used for acquiring and forsending temperature and accelerometer data.

The device 100 can reset its memory at predetermined intervals, based ontime, number of measurements or number of measurement intervals. Uponresetting, additional activation signals are not required for additionaldata gathering. The device 100 can transmit a join request upon reset.The device 100 can begin recording temperature and accelerationsregardless of whether the join request successfully establishes aconnection to the livestock management server. If a transmissioninterval elapses when the device 100 has not successfully connected, thedevice 100 can transmit the join request instead of the regular datapacket. The device 100 does not carry over old data between resets.

The battery life of the device 100 may be extended by collecting data atconfigurable intervals (e.g., 15 minutes, 30 minutes, or hourly or every2 hours). The systems and methods described herein can extend thebattery life of the device 100 by storing the collected data in a bufferto minimize the frequency of transmissions. For example, the device 100can transmit the collected data every 6 hours while collecting data inthe buffer every 15 minutes.

FIG. 10 depicts a firmware component diagram of the firmware loaded andrunning on the data processing system 235.

FIG. 11 depicts a firmware state diagram of the firmware loaded andrunning on the data processing system 235.

The acceleration component 1005 can interface with the accelerometer1010 to handle general acceleration use and features such asinitialization of the accelerometer 1010, the callback for when thememory is full, and packing and making rumination and activity dataavailable for the main component.

The activation component 1015 can handle the activation of the device100. The activation component 1015 can initialize the GPIO hardware tolook for interrupts generated by the closure of the magneticallyactivated reed switch 305 or other activation hardware. The activationcomponent 1015 can put the device to sleep until such interrupt istriggered. The activation component 1015 will not allow sleep unless thedevice 100 was previously activated. In other embodiments, otheractivation mechanisms may be used.

The activity component 1020 can provide function for computation ofactivity metrics based on acceleration data. The activity component 1020can include helper function for these computations.

The accelerometer component 1010 can include one or more functions forinterfacing with the accelerometer 225. The functions can includelow-level access of the command interface to the sensor as well as somehigher-level functions (e.g., self-test).

The identifier generator component 1025 can provide the interface forwriting to non-volatile memory. The device 100 can store severalcharacteristics in non-volatile memory. The identifier generatorcomponent 1025 may integrate the generation of the hardware acceleratedrandom number generator. The identifier generator component 1025 caninclude storage of both the application identifier and the hardwareidentifier to the EEPROM. The livestock management server can use theapplication identifier and the hardware identifier to identify thedevice 100. The data can be stored at predetermined addresses.

Cattle may be uniquely assigned an identification number, such as a CowID or other identifier provided by an agency such as the CanadianLivestock Tracking System, the Canadian Cattle Identification Agency,the International Committee for Animal Recording, the National AnimalIdentification System or some entity to which is delegated thisresponsibility by an agency. This identification number is unique to theindividual livestock animal, and may be centrally generated oradministered by an agency or delegated entity. Presently, Cow ID isnoted on an ear tag which must be affixed to the livestock animal. It isadvantageous not to use an ear tag which must be manually or opticallyread to hold this unique identifier, but rather to use a bolus such asthe device 100 to allow for electronic or automated reading of the CowID. The identifier generator component 1025 may store such anexternally-provided identifier, such as a Cow ID. The Cow ID may beprogrammed into an EEPROM, programmed into non-volatile memory, orstored in some other way accessible to the identifier generatorcomponent 1025. This programming may be performed at the time that thedevice 100 is manufactured, at a time when the manufacturer ordistributor acquires a Cow ID from an agency or delegated entity, at thetime that the device 100 is disposed within the livestock animal, or atsome other time. Ideally, the manufacturer of the device 100 receives anallocation of Cow IDs from the agency or delegated entity, selects oneCow ID from the allocation, programs the Cow ID into the device 100,prints a label with an optical code such as a QR code such that the QRcode encodes the Cow ID, and affixes the label to the device 100. Theoperator may then scan the label with the QR code to identify the CowID, and once device 100 is disposed within the livestock animal, maydirectly read out the Cow ID identifier through the network interface220. While Cow ID is the preferred identifier to use, any centrallyadministered identifier may be used.

The network component 1030 can include an expansion software pack. Thiscomponent can cause the network stack to permit and handle all networkprotocol requirements for transmission and reception. The networkcomponent 1030 can include preprocessor directives such as those toconfigure a geographic (e.g., North American) frequency band.Additionally, the channel mask can be configured to be compatible withthe local area network. The sub-components can be modified to use thespecified frequency bands and the application identifier to identify thedevice 100

The main component 1035 can integrate the components into anapplication. The main component 1035 can include functionality relatingto processor peripheral and initialization of the device 100. The maincomponent 1035 can include functionality relating to main loop. The maincomponent 1035 can include functionality relating to activationworkflow. The main component 1035 can be configured to self-test thedevice 100. The main component 1035 can include functionality relatingto transmission timers.

The rumination module 1040 can use the accelerometer data to estimatewhether rumination is detected in the livestock animal.

The temperature component 1045 can be configured to interface with thetemperature sensor. The functionality can include low-level access ofthe command interface to the sensor for initialization and receipt oftemperature measurements.

The transmitter component 1050 can provide two data structures for usein transmitting the sensor data. The transmitter component can provide acircular FIFO.

Upon boot up, the main component can initialize the peripherals (e.g.,temperature and accelerometer sensors) of the device 100. Once thesystem peripherals are initialized, the device 100 can be activated.

FIGS. 12 and 13 , among others, depict activation flow diagrams.Referring to FIG. 12 , among others, depicted is an activation flowdiagram. The device 100 can include an option to be activated onlybefore the application to the livestock animal. Prior to the activation,all device 100 can be OFF (e.g., no measuring and no accelerometerdata). The activation can be done by applying a magnet to a marked placeof the device to trigger activation. At the activation, the device 100can generate an alert (e.g., sound or light), so that the operator cansee the device is ON and ready to connect to a network.

Referring to FIG. 13 , among others, depicted is the activationworkflow. When the device 100 is activated and joined to the localnetwork, the device 100 can send a self-test packet to verify thehardware status. The accelerometer 225 can begin collecting data and thetemperature sensor 215 can begin collecting temperature measurements.The measurement timer can be set to a predetermined interval (e.g., 15minutes). The main loop can be entered and the device 100 can go tosleep.

The data processing system can wake under one or more conditions. Thenetwork protocol interrupts may cause the data processing system to wakeup. The low-power wide-area network interrupts can cause to processor toprocess MAC commands and downlinks from the network stack. Themeasurement timer expired interrupts can cause the data processingsystem to wake up. The measurement timer interrupts can cause the dataprocessing system to check if a transmission interval has elapsed. Ifthe transmission interval has elapsed, the data processing system canpack and transmit the relevant sensor data. The data processing systemcan check for the system reset interval. If the interval has elapsed,the data processing system can be reset. The accelerometer memory fullinterrupts can cause the data processing system to wake up. The memoryfull interrupt can trigger the accelerometer module callback function.The accelerometer is stopped and the accelerometer memory is clearedwhenever the processor is woken up. Such clearing of memory preventsunexpected function in the case where a memory interrupt would interruptother firmware processing.

FIG. 14 depicts a flow diagram for the accelerometer. Once activated,the device 100 can acquire acceleration data points from theaccelerometer. The memory of the accelerometer 225 can store apredetermined number of measurements before needing to be read. When thememory of the accelerometer is full, the accelerometer can send aninterrupt to the processor.

This interrupt can wake the processor to begin processing. The full FIFOcan be read from the accelerometer and used to calculate an activitymetric. The activity metrics are stored, the accelerometer is reset toacquire another measurement, and the data processing system can be putback to sleep.

When a predetermined number of memory overflows (e.g., 2, 4, 6, 8, 10 orother number of full FIFOs) have been processed and stored in this way,the device 100 can aggregate them by averaging the activity metrics andvoting (e.g., tie goes to rumination) with the rumination states. Theaggregate values are representative of a MX window (e.g., 15 minutes)and are made available to be read by other components. Since the timerequired to fill the memory the predetermined number of times (e.g., 2,4, 6, 8, or other number of FIFOs) can be slightly less (e.g., 800 sec)then the measurement interval (e.g., 900 sec), the measurements in theinterleaving time can be discarded. Other algorithms for estimating theactivity state from individual readings may be used, includingtime-weighted average, taking the most/least recent value, averagingwith a required threshold value, or some other algorithm

FIG. 15 depicts a network diagram for a livestock management server. Thelivestock management server can connect to the device 100 via networkservers and gateways, such as LoraWAN certified gateways. The livestockmanagement server can receive the transmissions from the device 100 atregular intervals, such as 15, 45, or 60 minutes. The livestockmanagement server can receive the transmissions in the format specifiedin the payload specification.

Data testing can include the operator activating the device 100 by theapplication of the magnet to generate the activation signal. The device100 can confirm the activation. The device 100 can acquire data for 24hours. The livestock management server can analyze variation in data(e.g. temperature changes, motion) for the sensors of the device 100.The livestock management server can pass the device 100 if the data wasreceived without packet loss for entire duration with sensor datareflecting the environment of the test.

Activation testing can include three unsuccessful activations followedby successful activation with magnet. The activation can be confirmed.The device 100 can acquire data for 24 hours. The livestock managementserver can analyze variation in data (e.g. temperature changes, motion)for the sensors of the device 100. The livestock management server canpass the device 100 if the data was received without packet loss forentire duration with sensor data reflecting the environment of the test.

Test reports can include identification of the test devices 100. Thetest report can include a picture of the test setup. The test report caninclude proof of activation. The test report can include proof ofactivation. The test report can include all data acquired during thetest. The data can be a separate file if filename is provided for reportand data to be packaged in compressed archive. The test report caninclude creating a template.

Post potting test includes setting up the device 100 to ignoreactivation. The device 100 can be activated with the magnet. The gatewayserver can receive the join message from the activated device 100. Thegateway server can confirm that the join messages were not accepted. Thelivestock management server can indicate that it is not activated. Thelivestock management server can be configured to ignore activation.

An advanced post-potting test can include firmware modifications. Thelivestock management server can be setup to accept activation. Thedevice 100 can be activated with a magnet. The device 100 can transmitdata packets and go back to sleep. The livestock management server canverify the data packets. The livestock management server can beconfigured to ignore the activation.

The device 100 can generate a self-test packet format for testing thedevice 100. The device 100 can send self-test packets when the device100 is activated. The packet can include bytes corresponding totemperature, and bytes corresponding to accelerometer health. The device100 can send the self-test packet via a predetermined port of thenetwork. The device 100 can transmit self-test status codes for testingthe accelerometer.

The device 100 can generate a temperature packet in a transmissionbuffer of the temperature sensor. The temperature sensor of the device100 can acquire temperature measurements. The measurements can be 16-bitmeasurement, taken at predetermined intervals and added to a circulartransmission FIFO that contains a predetermined number of measurements.

The device 100 can acquire movement data or acceleration activity datapoints from the accelerometer. The acceleration data can be included inactivity packets.

The device 100 can generate an acceleration packet in a transmissionbuffer of the accelerometer. A transmission buffer can include theacceleration information. The transmission buffer can be similar to thetransmission buffer to maintain a circular FIFO and redundancyproperties, measurement and transmission intervals (e.g., 15 and 45minutes respectively) like the temperature packets.

The livestock management server can perform data analysis on thetemperature and movement data. Based on the temperature data, thelivestock management server can identify a temperature of the livestockanimal. Based on the temperature data, the livestock management servercan identify a location of the livestock animal. For example, thelivestock management server can identify if the livestock animal isleaking based on the livestock animal having fewer digestive movements,abnormal movements, or abnormal locations. In yet another example, thelivestock management server can identify, based on the accelerometerdata, how often the livestock animal is chewing because the chewingwould cause movements identified by the accelerometer. If the livestockanimal is active, the livestock management server can identify if thelivestock animal is walking normally, staying still, or staggering. Thelivestock management server can track livestock animal activity patternsto see if the livestock animal is healthy or in heat. The livestockmanagement server can analyze the data to create metrics or performmachine learning on the accelerometer data. For example, the livestockmanagement server can sense water intake based on temperature changesinside the livestock animal's digestive tract. The livestock managementserver can use the data to generate a calving prediction of when thelivestock animal is about to give birth. The livestock management servercan use the data to identify eating efficiency of the livestock animal.The livestock management server can use accelerometer data within a timewindow to provide into a ML algorithm.

In an embodiment, the livestock management server can sense water intakeor feed intake based on temperature changes inside the livestockanimal's digestive tract. Digestive tract or rumen temperature maychange based on a number of factors, including water intake and feedintake.

As the animal drinks water, the rumen temperature drops quickly andreturns slowly to its baseline value in a characteristic way. As theanimal eats feed, the rumen temperature changes in a characteristic waydifferent from when the animal drinks water. Aspects of this measuredchange and return in temperature, such as total amount of temperaturedrop, longevity of the temperature drop, time to return to baseline ortime spent at a certain level below baseline, may correlate to a measureof total volume of water consumed by the animal, or to a measure oftotal mass of feed consumed by the animal. The livestock managementserver can calculate these statistical measures based on the temperaturemeasurement series, and may therefore estimate the amount of water orfeed consumed by the animal in this period of time. The livestockmanagement server may present this information to the user in the formof a report or user interface element, and may log this information on aper-animal basis.

In an embodiment, the livestock management server may use a machinelearning (ML) system to estimate the water or feed consumption of alivestock animal. The system may use similar inputs as an algorithmicapproach, may recognize characteristic changes in rumen temperaturewhich may correlate with periods of water consumption or feedconsumption, and may estimate water or feed consumption based on theseinputs.

In an embodiment, the device disposed within the livestock animal maycomprise a data processing element which implements a data analysismodule in order to provide smoother, more accurate, more timely orbetter interpreted data. The data analysis module may incorporatestatistical analysis algorithms, a machine learning (ML) algorithm orsystem, or some other data analysis system. The data analysis module mayreceive data from one or more sensors (e.g. accelerometer, temperaturesensor), and may output data in response to each new reading or mayaccumulate more than one reading before issuing output data. The dataanalysis module may output data with characteristics corresponding tosimilar characteristics of its inputs (e.g. receiving raw accelerometerreadings and outputting smoothed accelerometer values) or may outputdata with different characteristics from its inputs (e.g. receiving rawtemperature readings and outputting a signal corresponding to anestimate of whether the livestock animal is drinking).

In an embodiment, the livestock management server may receive readingsnot only from the inside of the livestock animal's digestive tract, butalso from one or more temperature or humidity or air quality sensorsoutside of the animal. Such sensors may be located in the animal's watersupply, in the animal's water trough or elsewhere in the water to sensethe water temperature, near or in the animal's feed supply, somewherewithin or nearby the building housing the animal in order to sense theair humidity or quality, or somewhere within or nearby the buildinghousing the animal in order to sense the air temperature, humidity orquality. The sensors may be located elsewhere for other readings. Thelivestock management server may improve the accuracy of the water intakeestimates by using a water temperature sensor reading or air temperaturesensor reading in conjunction with the rumen temperature reading toprovide a baseline reading for a heat transfer calculation, or to scalethe rumen sensor readings, or to provide one or more additional inputsfor a machine learning algorithm which estimates the animal's waterintake. Similar systems and methods may be used to improve the accuracyof the feed consumption estimates by using a temperature sensor readingin conjunction with the rumen temperature reading.

FIGS. 16 and 17 depict user interfaces for displaying livestock animalcharacteristics (e.g., behaviors, health, location, identification). Auser interface for a mobile phone 1605, a user interface for a tabletdevice 1610 and a user interface for a general-purpose computer (such asa desktop or laptop computer) 1615 are shown. The operator can establisha profile of the livestock animals. The livestock management server canmanage a range of normal parameters for each animal. The livestockmanagement server can crowdsource data to identify characteristics ofthe livestock animals. If the data from a device shows deviation fromthe early established norms of this animal, a notification (e.g., alert)can be sent to the operator's personal device (e.g., cellphone) or userinterface (e.g., web interface or portal). The livestock managementserver can receive feedback and confirmations from the operators torequest assessments to be used by the livestock management server toadjust sensitivity of the estimation and prediction algorithms. Thelivestock management server can increase precision for a particularlivestock animal or a particular farm or region. The farmer can providefeedback about the notification and the condition of the livestockanimal. This feedback can be used by the livestock management server totrain the ML algorithms to improve the accuracy of monitoring.Therefore, the system can incorporate the feedback and animal assessmentprotocols to continuously train the ML algorithms to improve theaccuracy and relevance of the alerts regarding the livestock animals.For example, if the livestock management server determines that a cowhas a fever but the farmer indicates that the cow does not have feverbut is simply hyperactive, the livestock management server can refinethe data analysis to identify that some cows are hyperactive instead ofhaving a fever. The data of a particular livestock animal or the entireherd can be shared with additional users such as veterinarians.

The livestock management server can apply rumination determination onthe received accelerometer data. The livestock management server canapply gradient decision tree or other algorithms to distill the data toa number between zero and 1 to identify a percentage of rumination. Thelivestock management server can use a machine learning algorithmsutilizing the raw data to perform rumination determination on thereceived data. The livestock management server can use the data toindicate a likelihood that the cow is ruminating during a particulartime. The livestock management server can calculate probabilities overtime and identify whether the livestock animal is ruminating based on apredetermined threshold (e.g., 30-70% above/below cutoff forrumination). The livestock management server can apply amplitudedeviation algorithms on the data.

The livestock management server can determine activities by testingactivity metrics and applying statistical measures to the received data.These statistical measures may be calculated on each element of receiveddata, on a sliding window of received data, or on some sampling of thereceived data.

The livestock management server can determine activities based on ENMO(Euclidian Norm Minus One), MAD (Mean Amplitude Deviation), AI (ActivityIndex), some other statistical measure related to the received data, orsome combination of these. These measures may be used to improve theaccuracy of the final output, to reduce noise in the output, to provideresults more quickly or with less data, to provide results which aremore generalizable, or to otherwise improve the information eventuallypresented to the operator.

According to the disclosure, a device to dispose within thegastrointestinal tract of a livestock ruminant animal is disclosed. Thedevice comprises a network interface, a housing that defines a cavity,the cavity including disposed therein, an identification tag, a weightedelement disposed at a first end of the cavity, a power source comprisinga capacitor and a battery, a temperature sensor coupled with the powersource, the temperature sensor to acquire temperature data of thelivestock animal, an accelerometer coupled with the power source, theaccelerometer to acquire movement data of the livestock animal, a dataprocessing system having at least one processor and memory, the dataprocessing system coupled with the power source and communicativelycoupled with the temperature sensor and the accelerometer, the memoryconfigured to store the temperature data and the movement data, the dataprocessing system to acquire the temperature data and the movement dataresponsive to the activation signal, the data processing system totransmit, via the network interface, the temperature data and themovement data, and an activation receiver to receive an activationsignal to activate the data processing system.

According to the disclosure, the activation receiver including a magnet.The housing includes a machine-acquirable identifier. The housingcomprises a biocompatible material. The housing has a weight between 50and 500 grams. The housing a width between 15 and 30 mm, and a lengthbetween 70 and 120 mm, such that the device may be disposed within thegastrointestinal tract of a newborn ruminating livestock animal. Thedevice further comprises a data processing system to receive from theserver, an acknowledgment of transmitting the temperature data and themovement data. The data processing system is configured to store a CowID identifier and to transmit the Cow ID identifier via the networkinterface.

According to the disclosure, the device connection request is a firstconnection request, wherein the connection is a first connection, andcomprising the data processing system to identify an error subsequent totransmitting the temperature data and the movement data, receive, fromthe temperature sensor of the device, additional temperature data of thelivestock animal, receive, from the accelerometer of the device,additional movement data of the livestock animal, transmit, responsiveto the activation signal, via the network interface, to the server, asecond connection request to establish a second connection with theserver and transmit, via the network interface using the secondconnection with the server, the temperature data, the movement data, theadditional temperature data, and the additional movement data.

According to the disclosure, the data processing system is configured toreceive temperature data from the temperature sensor, receive movementdata from the accelerometer, store the temperature data and the movementdata in the memory, generate a first data packet including thetemperature data stored in the memory, generate a second data packetincluding the movement data stored in the memory and transmit the datapackets including the temperature data and the movement data.

According to the disclosure, a device to manage livestock is disclosed.The device comprises a data processing system having one or moreprocessors coupled with memory. The data processing system is configuredto receive, from an activation receiver, an activation signal toactivate the data processing system, transmit, responsive to theactivation signal, via a network interface, to a server, a connectionrequest to establish a connection with the server, receive, from atemperature sensor of the device, temperature data of a livestockanimal, receive, from an accelerometer of the device, movement data ofthe livestock animal, store, in the memory of the data processingsystem, the temperature data and the movement data, transmit, via thenetwork interface using the connection with the server, the temperaturedata and the movement data.

According to the disclosure, a system to monitor livestock animals isdisclosed. The system comprises a herd database to maintain livestockanimal information of one or more livestock animals in a herd, a dataprocessing system having at least one processor coupled with memory, thedata processing system configured to receive, from a livestockmanagement device disposed within a livestock animal, a connectionrequest, the connection request including an identifier of the livestockmanagement device, identify, from the identifier of the livestockmanagement device, the livestock animal corresponding to the livestockmanagement device, receive, from the livestock management device,temperature data and movement data of the livestock animal, generate acomparison between the livestock animal information maintained by theherd database and the temperature data and movement data of thelivestock animal, identify, based on the comparison, estimated orpredicted characteristics of the livestock animal, transmit theestimated or predicted characteristics of the livestock animal to a userinterface, receive, from the user interface, an identification of thecharacteristic of the livestock animal and modify the analysis based onthe identification. The identifier is a machine-acquirable identifier

According to the disclosure, a method of managing livestock animal isdisclosed. The method comprising the steps of scanning an identifier ofa device, the device comprising a housing that defines a cavity, thecavity including disposed therein, an identification tag, a weightedelement disposed at a first end of the cavity, a power source comprisinga capacitor and a battery, a temperature sensor coupled with the powersource, the temperature sensor to acquire temperature data of thelivestock animal, an accelerometer coupled with the power source, theaccelerometer to acquire movement data of the livestock animal, a dataprocessing system having at least one processor and memory, the dataprocessing system coupled with the power source and communicativelycoupled with the temperature sensor and the accelerometer, the dataprocessing system to transmit, via the network interface, thetemperature data and the movement data and an activation receiver toreceive an activation signal to activate the data processing system. Themethod further comprises the steps of applying, using a magnetic field,the activation signal to activate the device, introducing the activateddevice into a gastrointestinal tract of the livestock animal, receiving,in a user interface, an estimated or predicted characteristic of thelivestock animal. The method further comprises the step of via the userinterface, providing a confirmed characteristic of the livestock animal.

According to the disclosure, a method to monitor livestock animals isdisclosed. The method comprises the steps of maintaining, by a dataprocessing system having at least one processor coupled with memory, aherd database including livestock animal information of one or morelivestock animals in a herd, receiving, by the data processing system,from a livestock management device disposed within a livestock animal, aconnection request, the connection request including an identifier ofthe livestock management device, identifying, by the data processingsystem, from the identifier of the livestock management device, thelivestock animal corresponding to the livestock management device,receiving, by the data processing system, from the livestock managementdevice, temperature data and movement data of the livestock animal,generating, by the data processing system, a comparison between thelivestock animal information maintained by the herd database and thetemperature data and movement data of the livestock animal, generating,by the data processing system, an analysis of the comparison to identifyestimated or predicted characteristics of the livestock animal,transmitting the estimated or predicted characteristics of the livestockanimal to a user interface, receiving, by the data processing system,from the user interface, a confirmed characteristic of the livestockanimal and modifying, by the data processing system, the informationmaintained by the herd database based on the confirmed characteristics.

According to the disclosure, a system to monitor livestock animals isdisclosed. The system comprises a herd database to maintain livestockanimal information of one or more livestock animals in a herd, a dataprocessing system having at least one processor coupled with memory, thedata processing system to receive, from a livestock management devicedisposed within a livestock animal, a connection request, the connectionrequest including an identifier of the livestock management device,identify, from the identifier of the livestock management device, thelivestock animal corresponding to the livestock management device,receive, from the livestock management device, temperature data of thelivestock animal, perform data analysis to detect periods when thelivestock animal likely drank water and extract statistical measuresfrom this data, generate an estimate of water consumption by thelivestock animal from the extracted statistical measures for at leastone period of likely water consumption and transmit the at least onewater consumption estimate of the livestock animal to a user interface.

According to the disclosure, the performance of data analysis of thesystem further comprises analyzing the temperature data received fromthe livestock management device. The system further comprises the dataprocessing system to receive a reading from a sensor external to thelivestock animal; and the performance of data analysis to compriseanalyzing the temperature readings from the data received from thelivestock management device and the sensor external to the livestockanimal. The performance of data analysis further comprises the use of amachine learning system trained to recognize periods of likely waterconsumption by the livestock animal from temperature data. The systemfurther comprises the data processing system to perform data analysis todetect periods when the livestock animal likely consumed feed andextract statistical measures from this data, generate an estimate offeed consumption by the livestock animal from the extracted statisticalmeasures for at least one period of likely feed consumption and transmitthe at least one feed consumption estimate of the livestock animal to auser interface.

According to the disclosure, a method of monitoring livestock animals isdisclosed. The method comprises the steps of maintaining, by a dataprocessing system having at least one processor coupled with memory, aherd database including livestock animal information of one or morelivestock animals in a herd, receiving, by the data processing system,from a livestock management device disposed within a livestock animal, aconnection request, the connection request including an identifier ofthe livestock management device, identifying, by the data processingsystem, from the identifier of the livestock management device, thelivestock animal corresponding to the livestock management device,receiving, by the data processing system, from the livestock managementdevice, temperature data of the livestock animal, performing, by thedata processing system, data analysis to detect periods when thelivestock animal likely drank water and extracting statistical measuresfrom this data, generating, by the data processing system, an estimateof water consumption by the livestock animal from the extractedstatistical measures for at least one period of likely waterconsumption, and transmitting the at least one water consumptionestimate of the livestock animal to a user interface.

Various elements, which are described herein in the context of one ormore embodiments, may be provided separately or in any suitablesubcombination. Further, the processes described herein are not limitedto the specific embodiments described. For example, the processesdescribed herein are not limited to the specific processing orderdescribed herein and, rather, process blocks may be re-ordered,combined, removed, or performed in parallel or in serial, as necessary,to achieve the results set forth herein.

Those skilled in the art may make various changes in the details,materials, and arrangements of the parts that have been described andillustrated herein without departing from the scope of the followingclaims.

All references, patents and patent applications and publications thatare cited or referred to in this application are incorporated in theirentirety herein by reference.

What is claimed is:
 1. A device to dispose within the gastrointestinaltract of a livestock ruminant animal comprising: a network interface; ahousing that defines a cavity, the cavity including disposed therein: anidentification tag; a weighted element disposed within the cavity; apower source comprising a capacitor and a battery; a temperature sensorcoupled with the power source, the temperature sensor to acquire atleast one of temperature data of the livestock animal temperature dataof the feed or temperature of water consumed by the livestock animal; anaccelerometer coupled with the power source, the accelerometer toacquire movement data of the livestock animal; a data processing systemhaving at least one processor and memory, the data processing systemcoupled with the power source and communicatively coupled with thetemperature sensor and the accelerometer, the memory configured to storethe temperature data and the movement data, the data processing systemto acquire the temperature data and the movement data, the dataprocessing system to transmit, via the network interface, thetemperature data and the movement data; and an activation receiver toreceive an activation signal to activate the data processing system;wherein the activation signal is a first connection request, andcomprising the data processing system to: receive, from the temperaturesensor of the device, additional temperature data of the livestockanimal; receive, from the accelerometer of the device, additionalmovement data of the livestock animal; transmit, responsive to theactivation signal, via the network interface, to the server, a secondconnection request to establish a connection with the server; andtransmit, via the network interface using a connection with the server,the temperature data, the movement data, the additional temperaturedata, and the additional movement data.
 2. The device of claim 1,comprising: the activation receiver including a magnet.
 3. The device ofclaim 1, comprising: the housing including a machine-acquirableidentifier.
 4. The device of claim 1, comprising: the housing having aweight between 50 and 500 grams.
 5. The device of claim 1, comprising:the housing comprising a biocompatible material.
 6. The device of claim1, comprising: the housing comprising a width between 15 and 30 mm, anda length between 70 and 120 mm, such that the device is configured to bedisposed within the gastrointestinal tract of a newborn ruminatinglivestock animal.
 7. The device of claim 1, comprising the dataprocessing system to: receive, from the server, an acknowledgment oftransmitting the temperature data and the movement data.
 8. The deviceof claim 1, comprising the data processing system configured to store aCow ID identifier and to transmit the Cow ID identifier via the networkinterface.
 9. The device of claim 1, comprising the data processingsystem to: receive temperature data from the temperature sensor; receivemovement data from the accelerometer; store the temperature data and themovement data in the memory; generate a first data packet including thetemperature data stored in the memory; generate a second data packetincluding the movement data stored in the memory; and transmit the datapackets including the temperature data and the movement data.
 10. Adevice to dispose within the gastrointestinal tract of a livestockruminant animal comprising: a network interface; a housing that definesa cavity, the cavity including disposed therein: an identification tag;a weighted element disposed at a first end of the cavity; a power sourcecomprising a capacitor and a battery; a temperature sensor coupled withthe power source, the temperature sensor to acquire temperature data ofthe livestock animal; an accelerometer coupled with the power source,the accelerometer to acquire movement data of the livestock animal; adata processing system having at least one processor and memory, thedata processing system coupled with the power source and communicativelycoupled with the temperature sensor and the accelerometer, the memoryconfigured to store the temperature data and the movement data, the dataprocessing system to acquire the temperature data and the movement dataresponsive to an activation signal, the data processing system totransmit, via the network interface, the temperature data and themovement data; and an activation receiver to receive the activationsignal to activate the data processing system; wherein the dataprocessing system is further configured to: receive temperature datafrom the temperature sensor; receive movement data from theaccelerometer; store the temperature data and the movement data in thememory; generate a first data packet including the temperature datastored in the memory; generate a second data packet including themovement data stored in the memory; and transmit the data packetsincluding the temperature data and the movement data.
 11. The device ofclaim 10, comprising: the activation receiver including a magnet. 12.The device of claim 10, comprising: the housing including amachine-acquirable identifier.
 13. The device of claim 10, comprising:the housing having a weight between 50 and 500 grams.
 14. The device ofclaim 10, comprising: the housing comprising a biocompatible material.15. The device of claim 10, comprising: the housing comprising a widthbetween 15 and 30 mm, and a length between 70 and 120 mm, such that thedevice may be disposed within the gastrointestinal tract of a newbornruminating livestock animal.
 16. The device of claim 10, comprising thedata processing system to: receive, from the server, an acknowledgmentof transmitting the temperature data and the movement data.
 17. Thedevice of claim 10, comprising the data processing system configured tostore a Cow ID identifier and to transmit the Cow ID identifier via thenetwork interface.
 18. The device of claim 10, wherein the activationsignal is a first connection request, and comprising the data processingsystem to: receive, from the temperature sensor of the device,additional temperature data of the livestock animal; receive, from theaccelerometer of the device, additional movement data of the livestockanimal: transmit, responsive to the activation signal, via the networkinterface, to the server, a second connection request to establish aconnection with the server; transmit, via the network interface using aconnection with the server, the temperature data, the movement data, theadditional temperature data, and the additional movement data.